Comments (1)
weihua916
commented on June 15, 2024
Hi! The goal of GIN is more of trying to capture the topological structure of nodes' neighborhood rather than smoothing the node features. The summation aggregation of GIN is suitable for capturing the topology, but if you apply it to social networks (some nodes have very high node degrees), you may suffer from exploding node feature problem due to the sum.
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Related Issues (20)
- dataset
- dataset HOT 2
- Data preprocessing HOT 2
- Reproduce Issues HOT 3
- Apply GIN to node classification HOT 5
- Problem.
- Dropout in last layer HOT 2
- Inconsistent dataset description and actual data HOT 1
- What is the meaning of the phrase "perform 10-fold cross-validation with LIB-SVM" in the paper? HOT 2
- Low accuracy HOT 6
- Cannot reproduce result on COLLAB！ HOT 2
- GIN's discriminative power for directed graph
- Ask for information of discrete labels
- About node attributes
- Think about graph spectral
- Custom dataset creation HOT 4
- COLLAB HOT 4
- result of paper HOT 3
- Possible bug in `load_data()` HOT 1
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